RMKL: Multiple Kernel Learning for Classification or Regression Problems

Provides R and C++ function that enable the user to conduct multiple kernel learning (MKL) and cross validation for support vector machine (SVM) models. Cross validation can be used to identify kernel shapes and hyperparameter combinations that can be used as candidate kernels for MKL. There are three implementations provided in this package, namely SimpleMKL Alain Rakotomamonjy et. al (2008), Simple and Efficient MKL Xu et. al (2010), and Dual augmented Lagrangian MKL Suzuki and Tomioka (2011) <doi:10.1007/s10994-011-5252-9>. These methods identify the convex combination of candidate kernels to construct an optimal hyperplane.

Getting started

Package details

AuthorChristopher Wilson, Kaiqiao Li
MaintainerChristopher Wilson <cwilso6@clemson.edu>
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

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RMKL documentation built on May 2, 2019, 7:55 a.m.